Q&A Hero

Question

Carlos Cavazos, Director of Human Resources, is exploring employee absenteeism at the Plano Piano Plant. A multiple regression analysis was performed using the following variables. The results are presented below.
Variable Description
Y number of days absent last fiscal year
x1 commuting distance (in miles)
x2 employee's age (in years)
x3 single-parent household (0 = yes, 1 = no)
x4 length of employment at PPP (in years)
x5 shift (0 = day, 1 = night)


Coefficients Standard Error t Statistic p-value
Intercept 6.594146 3.273005 2.014707 0.047671
x1 -0.18019 0.141949 -1.26939 0.208391
x2 0.268156 0.260643 1.028828 0.307005
x3 -2.31068 0.962056 -2.40182 0.018896
x4 -0.50579 0.270872 -1.86725 0.065937
x5 2.329513 0.940321 2.47736 0.015584


df SS MS F p-value
Regression 5 279.358 55.8716 4.423755 0.001532
Residual 67 846.2036 12.6299

Total 72 1125.562



R = 0.498191 R2 = 0.248194 Adj R2 = 0.192089
se = 3.553858 n = 73

Which of the following conclusions can be drawn from the above results?
a) All the independent variables in the regression are significant at 5% level.
b) Commuting distance is a highly significant (<1%) variable in explaining absenteeism.
c) Age of the employees tends to have a very significant (<1%) effect on absenteeism.
d) This model explains a little over 49% of the variability in absenteeism data.
e) A single-parent household employee is expected to be absent less number of days all other variables held constant compared to one who is not a single-parent household.

Answer

This answer is hidden. It contains 1 characters.

Related questions

Q: BigShots, Inc. is a specialty e-tailer that operates 87 catalog Web sites on the Internet. Kevin Conn, Sales Director, feels that the style (color scheme, graphics, fonts, etc.) of a Web site may affect its sales. He chooses three levels of design style (neon, old world and sophisticated) and randomly assigns six catalog Web sites to each design style. In Kevin's experiment "style" is _______.a) the dependent variableb) a treatment variablec) a concomitant variabled) a blocking variablee) a response variable
Q: While reviewing staffing plans for a new pilot plant, Colin Chenaux, VP of Operations at Clovis Chemicals, Inc., designed an experiment to test the effects of "supervisor's style" and "training method" on the productivity of operators. The treatment levels were: (1) authoritarian, and participatory for supervisor's style, and (2) technical manuals, training films, and multimedia for training method. Three qualified applicants were randomly selected and assigned to each of the six cells. In Colin's experiment, "operator productivity" is _____________. a) a concomitant variable b) a treatment variable c) the dependent variable d) a blocking variable e) a constant
Q: Data from a randomized block design are shown in the following table. Treatment Levels 1 2 3 4 Block 1 8 5 10 7 Block 2 6 6 9 5 Block 3 7 8 8 9 The Error Sum of Squares (SSE) is ________. a) 4.67 b) 12 c) 2.33 d) 28.67 e) 11
Q: Cindy Ho, VP of Finance at Discrete Components, Inc. (DCI), theorizes that the discount level offered to credit customers affects the average collection period on credit sales. Accordingly, she has designed an experiment to test her theory using four sales discount rates (0%, 2%, 4%, and 6%). First, she classified DCI's credit customers into three categories by total assets (small, medium, and large). Then, she randomly assigned four customers from each category to a sales discount rate. In Cindy's experiment "sales discount rate" is ________. a) a surrogate variable b) the dependent variable c) a blocking variable d) a treatment variable e) a constant
Q: Cindy Ho, VP of Finance at Discrete Components, Inc. (DCI), theorizes that the discount level offered to credit customers affects the average collection period on credit sales. Accordingly, she has designed an experiment to test her theory using four sales discount rates (0%, 2%, 4%, and 6%). First, she classified DCI's credit customers into three categories by total assets (small, medium, and large). Then, she randomly assigned four customers from each category to a sales discount rate. In Cindy's experiment "average collection period" is ________. a) a concomitant variable b) the dependent variable c) a treatment variable d) a blocking variable e) a constant
Q: For the following ANOVA table, the critical value of the studentized range distribution using a= 0.05 is ______ Source of Variation SS df MS F Treatment 36.17 2 18.08 5.66 Error 28.75 9 3.19 Total 64.92 11 a) 1.86 b) 3.94 c) 9.17 d) 1.65 e) 1.79
Q: Data from a completely randomized design are shown in the following table. Treatment Level 1 2 3 27 26 27 26 22 29 23 21 27 24 23 26 For a one-way ANOVA, the Error Sum of Squares (SSE) is ________. a) 36.17 b) 28.75 c) 64.92 d) 18.03 e) 28.04
Q: Data from a completely randomized design are shown in the following table. Treatment Level 1 2 3 27 26 27 26 22 29 23 21 27 24 23 26 For a one-way ANOVA, the Total Sum of Squares (SST) is ________. a) 36.17 b) 28.75 c) 64.92 d) 18.03 e) 28.04
Q: Cindy Ho, VP of Finance at Discrete Components, Inc. (DCI), theorizes that the discount level offered to credit customers affects the average collection period on credit sales. Accordingly, she has designed an experiment to test her theory using four sales discount rates (0%, 2%, 4%, and 6%) by randomly assigning five customers to each sales discount rate. An analysis of Cindy's data produced the following ANOVA table. Source of Variation SS df MS F Treatment 5.35 3 1.783333 Error 177.2 16 11.075 Total 182.55 19 Using a= 0.01, the appropriate decision is _________. a) reject the null hypothesism1= m2= m3= m4 b) reject the null hypothesism1 m2 m3 m4 c) do not reject the null hypothesis m1= m2= m3= m4 d) do not reject the null hypothesis m1 m2 m3m4 e) do nothing
Q: Cindy Ho, VP of Finance at Discrete Components, Inc. (DCI), theorizes that the discount level offered to credit customers affects the average collection period on credit sales. Accordingly, she has designed an experiment to test her theory using four sales discount rates (0%, 2%, 4%, and 6%) by randomly assigning five customers to each sales discount rate. In Cindy's experiment, "average collection period" is ________. a) the dependent variable b) a treatment variable c) a blocking variable d) a concomitant variable e) a constant
Q: BigShots, Inc. is a specialty e-tailer that operates 87 catalog Web sites on the Internet. Kevin Conn, Sales Director, feels that the style (color scheme, graphics, fonts, etc.) of a Web site may affect its sales. He chooses three levels of design style (neon, old world and sophisticated) and randomly assigns six catalog Web sites to each design style. Analysis of Kevin's data yielded the following ANOVA table. Source of Variation SS df MS F Between Groups 384.3333 2 192.1667 Within Groups 1359.667 15 90.64444 Total 1744 17 Using a= 0.05, the appropriate decision is _____________. a) do not reject the null hypothesism1 = m2 = m3 b) do not reject the null hypothesism1 m2 m3 c) reject the null hypothesis m1 m2 m3 d) reject the null hypothesis m1 m2 m3 e) do nothing
Q: BigShots, Inc. is a specialty e-tailer that operates 87 catalog Web sites on the Internet. Kevin Conn, Sales Director, feels that the style (color scheme, graphics, fonts, etc.) of a Web site may affect its sales. He chooses three levels of design style (neon, old world and sophisticated) and randomly assigns six catalog Web sites to each design style. Analysis of Kevin's data yielded the following ANOVA table. Source of Variation SS df MS F Between Groups 68102.33 2 34051.17 Within Groups 29177.67 15 1945.178 Total 97280 17 Using a= 0.05, the observed F value is _____________. a) 0.5022 b) 0.1333 c) 1.9911 d) 17.5100 e) 22.4567
Q: BigShots, Inc. is a specialty e-tailer that operates 87 catalog Web sites on the Internet. Kevin Conn, Sales Director, feels that the style (color scheme, graphics, fonts, etc.) of a Web site may affect its sales. He chooses three levels of design style (neon, old world and sophisticated) and randomly assigns six catalog Web sites to each design style. Analysis of Kevin's data yielded the following ANOVA table. Source of Variation SS df MS F Between Groups 68102.33 2 34051.17 Within Groups 29177.67 15 1945.178 Total 97280 17 Using a= 0.05, the critical F value is _____________. a) 3.57 b) 19.43 c) 3.68 d) 19.45 e) 2.85
Q: Pate's Pharmacy, Inc. operates a regional chain of 120 pharmacies. Each pharmacy's floor plan includes a greeting card department which is relatively isolated. Sandra Royo, Marketing Manager, feels that the level of lighting in the greeting card department may affect sales in that department. She chooses three levels of lighting (soft, medium, and bright) and randomly assigns six pharmacies to each lighting level. Analysis of Sandra's data yielded the following ANOVA table. Source of Variation SS df MS F Treatment 3608.333 2 1804.167 Error 13591.67 15 906.1111 Total 17200 17 Using a= 0.05, the appropriate decision is _____________. a) do not reject the null hypothesism1 m2 m3 b) do not reject the null hypothesism1 = m2 =m3 c) reject the null hypothesism1 m2 m3 d) reject the null hypothesism1 m2 m3 e) inclusive
Q: Medical Wonders is a specialized interior design company focused on healing artwork. The CEO, Kathleen Kelledy claims that artwork has healing effects for patients staying in a hospital, as measured by reduced length of stay. Her current client is a children's cancer hospital. Kathleen is interested in determining the effect of three different pieces of healing artwork on children. She chooses three paintings (a horse photo, a bright abstract, and a muted beach scene) and randomly assigns six hospital rooms to each painting. Analysis of Kathleen's data yielded the following ANOVA table. Source of Variation SS df MS F Treatment 33476.19 2 16738.1 9.457912 Error 26546.18 15 1769.745 Total 60022.37 17 Using a= 0.05, the critical F value is _____________. a) 13.68 b) 19.43 c) 3.59 d) 19.45 e) 3.68
Q: Medical Wonders is a specialized interior design company focused on healing artwork. The CEO, Kathleen Kelledy claims that artwork has healing effects for patients staying in a hospital, as measured by reduced length of stay. Her current client is a children's cancer hospital. Kathleen is interested in determining the effect of three different pieces of healing artwork on children. She chooses three paintings (a horse photo, a bright abstract, and a muted beach scene) and randomly assigns six hospital rooms to each painting. In Kathleen's experimental design "reduced length of stay" is _______. a) the dependent variable b) a concomitant variable c) a treatment variable d) a blocking variable e) a constant
Q: A human resources analyst is developing a regression model to predict electricity production plant manager compensation as a function of production capacity of the plant, number of employees at the plant, and plant technology (coal, oil, and nuclear). The "plant technology" variable in this model is ______. a) a response variable b) a dependent variable c) a quantitative variable d) an independent variable e) a constant
Q: A cost accountant is developing a regression model to predict the total cost of producing a batch of printed circuit boards as a linear function of batch size (the number of boards produced in one lot or batch), production plant (Kingsland, and Yorktown), and production shift (day, and evening). In this model, "shift" is ______. a) a response variable b) an independent variable c) a quantitative variable d) a dependent variable e) a constant
Q: The mean square error (MSerr) is calculated by dividing the sum of squares error (SSerr) by the number of error degrees of freedom (dferr).
Q: Annie Mikhail, market analyst for a national company specializing in historic city tours, is analyzing the relationship between the sales revenue from historic city tours and the size of the city. She gathers data from six cities in which the tours are offered. Annie's dependent variable is annual sales revenues and her independent variable is the city population. Regression analysis of the data yielded the following tables. Coefficients Standard Error t Statistic p-value Intercept -0.14156 0.292143 -0.48455 0.653331 x 0.105195 0.013231 7.950352 0.001356 Source df SS MS F Se = 0.237 Regression 1 3.550325 3.550325 63.20809 r2 = 0.940483 Residual 4 0.224675 0.056169 Total 5 3.775 For a city with a population of 500,000, Annie's model predicts annual sales of ________________. a) $70,780 b) $5,259 c) $170,780 d) $52,597 e) $152,597
Q: Annie Mikhail, market analyst for a national company specializing in historic city tours, is analyzing the relationship between the sales revenue from historic city tours and the size of the city. She gathers data from six cities in which the tours are offered. Annie's dependent variable is annual sales revenues and her independent variable is the city population. Regression analysis of the data yielded the following tables. Coefficients Standard Error t Statistic p-value Intercept -0.14156 0.292143 -0.48455 0.653331 x 0.105195 0.013231 7.950352 0.001356 Source df SS MS F Se = 0.237 Regression 1 3.550325 3.550325 63.20809 r2 = 0.940483 Residual 4 0.224675 0.056169 Total 5 3.775 Annie's sample size is __________. a) 2 b) 4 c) 6 d) 8 e) 10
Q: Annie Mikhail, market analyst for a national company specializing in historic city tours, is analyzing the relationship between the sales revenue from historic city tours and the size of the city. She gathers data from six cities in which the tours are offered. Annie's dependent variable is annual sales revenues and her independent variable is the city population. Regression analysis of the data yielded the following tables. Coefficients Standard Error t Statistic p-value Intercept -0.14156 0.292143 -0.48455 0.653331 x 0.105195 0.013231 7.950352 0.001356 Source df SS MS F Se = 0.237 Regression 1 3.550325 3.550325 63.20809 r2 = 0.940483 Residual 4 0.224675 0.056169 Total 5 3.775 Annie's regression model can be written as: __________. a) y = 7.950352 - 0.48455x b) y = -0.48455 + 7.950352x c) y = -0.14156 + 0.105195x d) y = 0.105195 - 0.14156x e) y = 0.105195 + 0.14156x
Q: A manager wants to predict the cost (y) of travel for salespeople based on the number of days (x) spent on each sales trip. The following model has been developed: y = $400 + 120x. If a trip took 4 days, the predicted cost of the trip is _____________. a) 480 b) 880 c) 524 d) 2080 e) 1080
Q: In the regression equation, y=2.164+1.3657x n=6, the mean of x is 8.667, Sxx=89.333 and Se=3.44. A 95% prediction interval for y when x=8 is _________ a) (9.13, 17.05) b) (2.75, 23.43) c) (10.31, 15.86) d) (3.56, 22.62) e) (12.09, 14.09)
Q: A researcher has developed a regression model from fourteen pairs of data points. He wants to test if the slope is significantly different from zero. He uses a two"‘ tailed test and a = 0.01. The critical table t value is _______. a) 2.650 b) 3.012 c) 3.055 d) 2.718 e) 2.168
Q: In a regression analysis if SST = 200 and SSR = 200, r 2 = _________. a) 0.25 b) 0.75 c) 0.00 d) 1.00 e) -1.00
Q: The proportion of variability of the dependent variable accounted for or explained by the independent variable is called the _______. a) sum of squares error b) coefficient of correlation c) coefficient of determination d) covariance e) regression sum of squares
Q: The numerical value of the coefficient of determination must be _______. a) between -1 and +1 b) between -1 and 0 c) between 0 and 1 d) equal to SSE/(n-2) e) between -100 and +100
Q: A standard deviation of the error of the regression model is called the _______. a) coefficient of determination b) sum of squares of error c) standard error of the estimate d) R-squared e) coefficient of correlation
Q: The following residuals plot indicates _______________. a) a nonlinear relation b) a nonconstant error variance c) the simple regression assumptions are met d) the sample is biased e) the sample is random

Subjects

Accounting Anthropology Archaeology Art History Banking Biology & Life Science Business Business Communication Business Development Business Ethics Business Law Chemistry Communication Computer Science Counseling Criminal Law Curriculum & Instruction Design Earth Science Economic Education Engineering Finance History & Theory Humanities Human Resource International Business Investments & Securities Journalism Law Management Marketing Medicine Medicine & Health Science Nursing Philosophy Physic Psychology Real Estate Science Social Science Sociology Special Education Speech Visual Arts